Over the past decade, the advent of modern digital advertising technologies has transformed many forms of digital advertising. One hallmark of these digital advertising technologies (collectively referred to as “programmatic” advertising) is the ability to bid electronically on digital advertising opportunities, either in real-time, using so-called “real-time bidding” (RTB) techniques or in advance using so-called “private deal” techniques, via electronic platforms. Programmatic techniques for electronic bidding, including RTB and private deals, via digital ad buying systems enables buyers (e.g., agencies or advertisers) to electronically identify, and with a high level of precision, electronically target their digital advertisements and bid on exactly the electronic devices that best meet their business objectives for the digital advertisements to be placed. Programmatic digital advertising technology also enables buyers to directly associate subsequent consumer actions via the electronic devices (e.g., visiting a website or making an online purchase, to name a few) with the prior delivery of a digital advertisement, via a process called “attribution” that links the two events via a common identifier. The attribution process seeks to associate digital advertisements shown to a consumer and subsequent actions taken by the consumer. When the two events occur on different devices, the process is known as “cross-device attribution.”
These programmatic benefits of precise targetability (via electronic bidding) and impact measurement (via attribution) have driven massive growth in many forms of digital advertising, including online display advertising, online video advertising, mobile advertising, social media advertising, and others—typically delivered on personal electronic devices such as laptop computers, desktop computers, smartphones, tablets, and other personal electronic devices.
However, it has not hitherto been possible to obtain these benefits in the context of digital advertising on a non-personal digital device, such as devices that may be in a public or semi-public setting (e.g., digital advertising displayed on digital billboards, on street kiosks, on trains or buses, in elevators, in taxis, in restaurants, in health clubs, in movie theaters, and/or in airports, to name a few) because of several technical reasons.
One technical issue associated with current digital ad buying systems, is that digital advertising delivered on personal electronic devices is assumed to be seen by one individual—e.g., a user of the personal electronic device. By contrast, digital advertising on a non-personal digital device in a public or semi-public setting may be seen by more than one individual, and often by many individuals, at the same time. Current programmatic techniques do not provide a technological solution to address the technical issues created by the situation involving multiple distinct individuals exposed to a single advertisement on a non-personal digital device. Efforts to date have focused on automating the buying of digital advertising on non-personal digital devices, but have failed to produce the capability using technology to track individual instances of the digital advertisements delivered to individual consumers (“impressions”). Some existing methods and systems attempt to record a so-called “impression multiplier” corresponding to the estimated number of consumers exposed to an advertisement on a non-personal digital device. However, these methods and systems suffer from technical drawbacks since they do not create individual atomic records of each impression, nor do they allow the capture of unique identifiers that can power attribution.
Another technical issue associated with current digital advertising systems arises because digital advertising delivered on personal electronic devices leverages the fact that those devices belong to specific individuals and typically have device-specific advertising identifiers (also referred to herein as “advertising identifiers”) that can be used to recognize the device (which is then a proxy for the individual). Those identifiers are used to uniquely identify the advertising event and associate that event with a subsequent event on the same device (via same-device attribution) or another device belonging to the same individual (via cross-device attribution). By contrast, digital advertising on a non-personal digital device in a public or semi-public setting is, by definition, delivered on devices that have no association to the individuals seeing the advertising, and digital ad buying systems today have no means to associate subsequent events taken by the individuals exposed to the advertising in question. Efforts to date have focused on measuring aggregate statistical impact of exposure to digital advertising on non-personal digital devices (e.g., via surveys of exposed users or other sampling approaches), or on narrowly measuring direct consumer response to digital advertising on non-personal digital devices via some immediate call to action (e.g., scanning a unique QR code), but have failed to produce any technology to associate, within a digital ad buying system or an integrated measurement platform, subsequent consumer actions (e.g., visiting a website or making an online purchase) on a personal electronic device taken after the ad exposure on a non-personal digital device.
What is needed is a way to solve these technological problems with existing digital buying systems to enable (a) electronic bidding on digital advertising on non-personal digital devices, and (b) subsequent consumer actions taken on personal electronic devices to be attributed to such digital advertising.